Akash Deep Singh

Computer Vision & Machine Learning Engineer

Tessellate Imaging

Matlab 3 years
Python 3 years


I am passionate about combining Artificial Intelligence and Machine Vision. I have worked for building novel systems to detect; classify glioma cancer and a real-time stat generation camera solution for basketball players. I was also part of the team which built India’s first panoramic camera where I acted as the Machine Learning Lead. My past projects include autopilot firmware for search and rescue drones, building disguised and imposter's face recognition software, an all-terrain navigation vehicle, and sketch to face image matching for forensics.

My Publications-
1. Analysis and optimization of parameters used in training a cascade classifier
Published in Journal, Advances in Image and Video Processing, Society for Science and Education, United Kingdom, ISSN: 2054-7412, Vol:3, Issue: 3, April 2015
Short Description:
This paper is published in association with Ayonix - Face recognition company, Japan. This Research is focused on optimizing the parameters used in Local Binary pattern and Histogram of gradients based cascade classifiers.

2. A Novel System to Monitor Illegal Sand Mining Using Contour Mapping and Color based Image Segmentation
Published in Journal, International Journal of Image Processing, Computer Science Journals, Kuala Lumpur, Malaysia.ISSN: 1985-2304, Vol: 9, Issue: 3, June 2015
Short Description:
The work is done under the guidance of Whishworks, Hyderabad. This Research was done on implementing a sand mining monitoring system.

SOFT SKILLS:

Positive Attitude
  4.5 / 5
Team work
  4.5 / 5
Responsibility
  4.4 / 5
Flexibility
  4.6 / 5
Problem Solving
  4.7 / 5
Leadership
  4.3 / 5

WORK PERSONA

English communication
  4.6 / 5
Past work clarity
  4.7 / 5
Client interaction experience
  4.5 / 5
Transparency
  4.5 / 5
Open to learning
  4.6 / 5
Open source contribution
  4.3 / 5

INDUSTRIES SERVED

EducationMedicalNavigationPhoto & Video

PAST WORK

  • Real-time Basketball Statistics generation using Monocular Camera

    ML Engineer

    Python 3.6C++Embedded CTensorflowOpenCV

    Using a monocular camera setup, tracking basketball players throughout a game or practice session to generate player statistics in real-time.

  • Semantic segmentation and classification of Glioma cancer from histopathology slides

    ML Engineer

    PythonCaffeDIGITSTheanoOpenCVScikit-Image

    Automating detection of cancerous regions of glioma cancer(Brain cancer) using Deep Learning based semantic classification of histopathology slides achieving state of the art results.

  • Face detection and Disguised Face recognition system

    Engineer

    PythonLuaTorchPyTorchCaffe2

    A Deep Learning based implementation for detection and counting faces in heavily occluded scenes and to distinguish disguised and imposter's face.

  • A Novel System to Monitor Illegal Sand Mining using Contour Mapping and Color based Image Segmentation

    Computer Vision Engineer

    PythonJavaOpenCVTensorflowXamarin

    This system includes a novel vehicle detection approach for detecting vehicles from static images and calculating the amount of sand being carried to prevent the malpractices of sand smuggling. Different from traditional methods, which use machine learning to detect vehicles, this method introduces a new contour mapping model to find important "vehicle edges" for identifying vehicles The sand detection algorithm uses color based segmentation since sand can have various colors under different weather and lighting conditions The proposed new color segmentation model has excellent capabilities to identify sand pixels from background, even though the pixels are lighted under varying illuminations.

  • Automatic Search and Rescue Drone

    ML Engineer

    PythonJavaOpenCVCEmbedded C

    This system uses a Human detection algorithm for onboard search and location in disaster-hit areas. Successful implementation of an efficient Human Detection and path planning algorithm for faster search and rescue operations.